Abstract
Community leaders are individuals who have huge influence on social network communities. Discovering community leaders in social networks is of great significance for research on the structures of the social networks and for commercial application. Based on the core idea of the PageRank algorithm, this paper firstly processes data selected from Sina microblog, and extracts three key indicators, comprising the number of followers, the number of comments and the number of reposts; then based on their mutual relationship, that is following or followed, it obtains the weight of influence for each individual user; and then after a finite number of iterations, this paper identifies the community leader in Sina microblog, by which its comprehensive influence on its community are reflected.
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Wang, R., Zhang, W., Deng, H., Wang, N., Miao, Q., Zhao, X. (2013). Discover Community Leader in Social Network with PageRank. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7929. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38715-9_19
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DOI: https://doi.org/10.1007/978-3-642-38715-9_19
Publisher Name: Springer, Berlin, Heidelberg
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Online ISBN: 978-3-642-38715-9
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